Psychopathology, social adjustment and personality correlates of schizotypy clusters in a large nonclinical sample

Schizophrenia Research xxx (2010) xxx–xxx

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Psychopathology, social adjustment and personality correlates of schizotypyclusters in a large nonclinical sample

Neus Barrantes-Vidal a,b,c, Kathryn E. Lewandowski d, Thomas R. Kwapil e,⁎a Universitat Autònoma de Barcelona, Spainb Sant Pere Claver-Fundació Sanitària, Spainc CIBER Salud Mental, Instituto de Salud Carlos III, Spaind Harvard Medical School, United Statese University of North Carolina at Greensboro, United States

a r t i c l e i n f o

⁎ Corresponding author. Department of PsychNorth Carolina at Greensboro, P.O. Box 26170, GreensUnited States. Tel.: +1 336 256 0003; fax: +1 336 334

E-mail address: [email protected] (T.R. Kwapil).

0920-9964/$ – see front matter © 2010 Elsevier B.V.doi:10.1016/j.schres.2010.01.006

Please cite this article as: Barrantes-Vidschizotypy clusters in a large nonclinical

a b s t r a c t

Article history:Received 28 November 2009Received in revised form 7 January 2010Accepted 11 January 2010Available online xxxx

Introduction: Correlational methods, unlike cluster analyses, cannot take into account thepossibility that individuals score highly onmore than one symptom dimension simultaneously.This may account for some of the inconsistency found in the literature of correlates ofschizotypy dimensions. This study explored the clustering of positive and negative schizotypydimensions in nonclinical subjects and whether schizotypy clusters have meaningful patternsof adjustment in terms of psychopathology, social functioning, and personality.Methods: Positive and negative schizotypy dimensional scores were derived from the ChapmanPsychosis-Proneness Scales for 6137 college students and submitted to cluster analysis. Of these,780 completed the NEO-PI-R and Social Adjustment Scale-self report version, and a further 430were interviewed for schizophrenia-spectrum, mood, and substance use psychopathology.Results: Four clusterswereobtained: low(nonschizotypic), highpositive, highnegative, andmixed(high positive and negative) schizotypy. The positive schizotypy cluster presented high rates ofpsychotic-like experiences, schizotypal and paranoid symptoms, had affective and substanceabusepathology, andwas open to experience and extraverted. Thenegative schizotypy cluster hadhigh rates of negative and schizoid symptoms, impaired social adjustment, high conscientiousnessand low agreeableness. The mixed cluster was the most deviant on almost all aspects.Conclusions: Our cluster solution is consistent with the limited cluster analytic studies reported inschizotypy and schizophrenia, indicating that meaningful profiles of schizotypy features can bedetected in nonclinical populations. The clusters identified displayed a distinct and meaningfulpattern of correlates in different domains, thus providing construct validity to the schizotypy typesdefined.

© 2010 Elsevier B.V. All rights reserved.

Keywords:SchizotypySchizophreniaCluster analysisPsychopathologyPersonalitySocial adjustment

1. Introduction

Factor analytic studies of the symptoms of schizophrenia(Peralta et al., 1992) and schizotypy (Stefanis et al., 2004)support a common underlying structure with at least threedimensions: positive, negative, and disorganized. Alterna-

ology, University ofboro, NC 27402-6170,5066.

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al, N., et al., Psychopasample, Schizophr. Res.

tively, cluster analysis (Everitt, 1993) can be used to examinewhether individuals fall into distinct groups that reflect thedimensions identified by factor analytic studies (Suhr andSpitznagel, 2001a). It can also clarify inconsistencies found incorrelational studies that attempt to resolve the heterogene-ity of schizophrenia and schizotypy by relating specificsymptom dimensions with psychopathology and impair-ment. Correlational methods do not take into account thepossibility that schizotypes are elevated on more than onedimension simultaneously (Walker and Lewine, 1988).Therefore, a study with a predominance of subjects with a

thology, social adjustment and personality correlates of(2010), doi:10.1016/j.schres.2010.01.006

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pure profile of positive symptoms may find an associationbetween the positive dimension and a given measure;however, this relationmay turn out to beweak or nonexistentin another study in which subjects have a mixed profile ofhigh positive and negative schizotypy (Suhr and Spitznagel,2001a). Therefore, cluster analytic studies provide a goodcomplement to factor analytic approaches.

The few cluster analytic studies conducted in schizophreniaindicate that not all patients fit into groups defined by therelatively orthogonal dimensions yielded by factor analyticstudies. The consistent picture across schizophrenia studies isthat clusters of high positive, high negative, and mixed (highpositive and negative) symptoms emerge (Dollfus et al., 1996;Lykouras et al., 2001; Mohr et al., 2004; Morrison et al., 1990;Williams, 1996), with other clusters depending on the numberand nature of dimensions included in the analyses. Similarly,schizotypy studies typically find positive, negative, mixed, andlow schizotypy clusters (Aguilera et al., 2008; Barrantes-Vidalet al., 2003; Goulding, 2004, 2005; Loughland and Williams,1997; Suhr and Spitznagel, 2001a,b; Williams, 1994). Thenature of the “mixed cluster” depended on the particulardimensions included in the studies. Suhr and Spitznagel(2001a) used the Schizotypal Personality Questionnaire (SPQ;Raine, 1991), which includes positive, negative and disorga-nized dimensions, and identified a mixed cluster high on allthree dimensions; whereas Barrantes-Vidal et al. (2003) usedthe Chapman Psychosis-Proneness scales and found a mixedcluster consisting of positive and negative schizotypy.

A number of studies have examined the correlates ofschizotypy dimensions. Dinn et al. (2002) reported differen-tial patterns of correlations of positive and negative schizo-typy clusters. Lewandowski et al. (2006) reported thatpositive, but not negative, schizotypy was related to symp-toms of depression and anxiety. Recently, Kwapil et al. (2008)found that both dimensions were related to schizotypal andparanoid personality disorder symptoms, whereas positiveschizotypy was uniquely related to psychotic-like experi-ences, substance abuse, mood disorders, and history ofmental health treatment, and negative schizotypy wasspecifically associated with negative and schizoid symptoms.Both dimensions were associated with poorer overall andsocial functioning.

However, only two studies have examined behavioralcorrelates of schizotypy clusters. Suhr and Spitznagel (2001b)reported that participants high on their mixed schizotypycluster were rated poorer on a behavior rating scale thanparticipants in the positive, negative and low schizotypyclusters. However, as the authors pointed out, the wide rangeof unusual behaviors were not subdivided into meaningfulsubscales, rendering it difficult to interpret the findings.Barrantes-Vidal et al. (2003) found that adolescents in thehigh positive and negative schizotypy cluster received poorerratings on the Achenbach (1991) Teacher Report Form than inthe other clusters.

The goal of the present study was to examine the clusterstructure of positive and negative schizotypy in a largenonclinically ascertained sample of young adults. We hy-pothesized that most participants would fall in a lowschizotypy cluster, and that the large sample size wouldallow for the characterization of three distinctive schizotypyclusters: high positive schizotypy, high negative schizotypy,

Please cite this article as: Barrantes-Vidal, N., et al., Psychopschizotypy clusters in a large nonclinical sample, Schizophr. Res.

and high positive and negative schizotypy (mixed) clusters.The second aim was to examine the validity of the schizotypyclusters by examining ratings of psychopathology, personal-ity, and impairment. Based on the findings from correlationalstudies (as no schizotypy cluster study has addressed thisissue), we expected that the positive cluster would beassociated with schizotypal, paranoid and psychotic-likesymptoms, social distress, and mood disorders, as well ashigh neuroticism and openness to experience. The negativeschizotypy cluster was expected to be characterized byschizotypal, schizoid, paranoid, and negative symptoms,social impairment, and low extraversion and openness.Consistent with previous cluster studies, it was expectedthat the hypothesizedmixed schizotypy clusterwould exhibitthe highest level of symptoms and impairment.

2. Methods

2.1. Subjects

Usable Chapman Psychosis-Proneness questionnaireswere completed by 6137 undergraduates enrolled at theUniversity of North Carolina at Greensboro (UNCG) between1998 and 2005 (this sample and correlational results withthese measures were described in Kwapil et al., 2008). Themean age was 19.4 (SD=3.7). Consistent with universitydemographics, the sample was 76% female and 24% male.

An unselected subset of 780 participants completedquestionnaire measures of personality and social functioning.The subsample was comparable to the original sample with75% female and 25%male and amean age of 19.3 (SD=3.4). Asubset of 430 participants underwent structured diagnosticinterviews. Likewise, this subsample was comparable to theoriginal sample with 74% female and 26% male and a meanage of 19.2 (SD=1.4). Participants were recruited for inter-views based upon their scores on the Chapman Psychosis-Proneness scales as part of several studies conducted atUNCG. Both subsamples were comparable to the originalsample in terms of age and sex. A total of 184 participantswere included in both subsamples.

2.2. Materials and procedures

Participantswere administered theMagical Ideation (Eckbaldand Chapman, 1983), Perceptual Aberration (Chapman et al.,1978), Physical Anhedonia (Chapman et al., 1976), and RevisedSocial Anhedonia (Eckblad, et al., 1982) Scales. The items wereintermixed with a 13-item measure of infrequent responding(Chapman and Chapman, 1983) included to screen out invalidprotocols. Participantswhoendorsedmore than two infrequencyitems were dropped from further study. Participants completedthe NEO-PI-R (Costa and McCrae, 1992) and the SocialAdjustment Scale (SAS; Weissman, 1999). The NEO-PI-R is awidely used self-report measure of the Five-Factor Model ofpersonality. This model assumes that adaptive and pathologicalaspects of personality can be accounted for by variation in fivebasic dimensions: neuroticism, extraversion, openness to expe-rience, agreeableness, and conscientiousness (each of which areassessed by the questionnaire). The SAS assesses functioning in avariety of social contexts. It provides a total score and threesubscale scores applicable to college students that assess social

athology, social adjustment and personality correlates of(2010), doi:10.1016/j.schres.2010.01.006

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functioning in school, during social and leisure activities, andwith family, with higher scores indicating greater impairment.

The interview contained portions of the Structured ClinicalInterview for DSM-IV (First et al., 1995) that assesses moodepisodes, substance use disorders, and demographic informa-tion. Quantitative ratings of substance use and impairmentwere made using the system described in Kwapil (1996). Themodules of the International Personality Disorders Examina-tion (IPDE; World Health Organization, 1995) that assessschizoid, paranoid, and schizotypal personality disorders wereincluded. The IPDE provides personality disorders diagnosesand dimensional ratings.

The Wisconsin Manual for Assessing Psychotic-like Experi-ences (Chapman and Chapman, 1980; Kwapil et al., 1999) andthe Negative Symptom Manual (Kwapil and Dickerson, inpress) were used to quantify psychotic and negative symptomsof schizophrenia across a broad range of clinical and subclinicaldeviancy. The Global Assessment Scale (GAS; Endicott et al.,1976) was used to assess participants' overall functioning. Theinterviews were conducted by a licensed clinical psychologistand advanced graduate students in clinical psychology, whowere unaware of participants' schizotypy cluster assignment.

3. Results

3.1. Cluster assignment and identification

Aldenderfer and Blashfield (1984) cautioned against in-cluding highly correlated scales in cluster analyses and, in suchcases, recommended performing principal components analy-sis to extract underlying dimensions prior to conducting clusteranalysis. Given the intercorrelations among the schizotypyscales, we performed a principal components analysis on thefour scales using a promax rotation. The analysis producedpositive and negative schizotypy factors that accounted for 80%of the variance. Similar to the original schizotypymeasures, thedistributions of the two component scores were positivelyskewed. Following Blashfield, we performed square-roottransformations to normalize the data. We then performed a

Table 1Cluster characteristics for the derivation (n=6137), questionnaire (n=780), and i

Cluster

Positive schizotypy Negative schizotypy Mixed

Derivation sample n(%) 1.895(31) 1.352(22) 753(1Positive dimension score 0.80 (0.89) −0.60 (0.45) 1.04 (Negative dimension score −0.36 (0.47) 1.03 (0.82) 1.23 (% Male/female 21.9/78.1 33.7/66.3 30.9/6

Questionnaire Sample n(%) 213(27) 169(22) 107(1Positive dimension score 0.82 (0.92) −0.57 (0.47) 1.23 (Negative dimension score −0.37 (0.48) 1.20 (1.00) 1.28 (% Male/female 22.5/77.5 39.6/60.4 29/71

Interview sample n(%) 124(29) 117(27) 88(20Positive dimension score 1.44 (1.27) −0.48 (0.50) 1.52 (Negative dimension score −0.44 (0.52) 1.63 (1.04) 1.64 (% Male/female 22.6/77.4 31.6/68.4 22.7/7

***p<0.001; **p<0.01*p<0.05.Values reflect mean (standard deviation). Post hoc comparisons were computed usoriginal derivation sample. The questionnaire and interview subjects are subsets fromMixed; P: Positive; N: Negative; L: Low schizotypy.

Please cite this article as: Barrantes-Vidal, N., et al., Psychopaschizotypy clusters in a large nonclinical sample, Schizophr. Res.

K-means iterative cluster analysis with the two dimensionalscores. K-means iterative cluster analyses handle larger datasets better than hierarchical agglomerativemethods. Followingprevious existing cluster studies in schizotypy (Barrantes-Vidalet al., 2003; Loughland and Williams, 1997; Suhr andSpitznagel, 2001a,b; Williams, 1994, 1995), we forced a four-cluster solution. We then carried out a MANOVA using thecluster assignment as the independent variable and theschizotypy dimension scores as the dependent variables inorder to obtain a discriminative index for the clusters. Wilks'Lambda (0.126) was significant, p<0.001, indicating that withthe three canonical functions generated in the analysis only left13% of the total variance unexplained. Table 1 presents thesample size aswell as themeans and standarddeviationson thepositive and negative schizotypy dimensions for each of thefour clusters. Given the clear composition of the groupings, welabelled them positive schizotypy, negative schizotypy, mixedschizotypy, and low (or control) schizotypy clusters. Table 1also presents the cluster characteristics for the interview andquestionnaire samples.

3.2. Validity of the schizotypy clusters

In order to examine the validity of the schizotypy clusters, aseries of one-way ANOVAs was conducted comparing theclusters on interview measures of psychopathology andquestionnaire measures of personality and adjustment. Notethat MANOVAs were not conducted due to the differentpredictions for the clusters across measures. Post hoc compar-isons of the groups were computed using Newman–Keuls test.In the case of categorical data, Fisher's exact test was used tocompute the six pairwise comparisons between the clusters. Inorder to control for Type 1error, alphawas set at 0.008 (0.05/6).

3.2.1. Relationship with interview measures of psychopathologyTable 2 presents the comparison of the four clusters on

interview measures of psychopathology. Table 3 presents thecomparison on categorical measures of impairment. As hypoth-esized, the mixed schizotypy cluster demonstrated the most

nterview samples (n=430).

schizotypy Low schizotypy F Significant comparisons

2) 2.137(35) df=3, 61330.78) −0.69 (0.42) 2791.7*** M>P>N>L0.68) −0.76 (0.44) 3945.8*** M>N>P>L9.1 17.3/82.7 χ2=145.91***4) 291(37) df=3, 7760.90) −0.67 (0.43) 357.0*** M>P>N,L0.68) −0.81 (0.50) 507.4*** M,N>P>L

17.2/82.2 χ2=30.29***) 101(24) df=3, 4260.90) −0.69 (0.38) 207.5*** M,P>N,L0.81) −0.80 (0.45) 327.5*** M,N>P>L7.3 24.8/75.2 χ2=3.24*

ing Newman–Keuls test. Note that cluster assignments were based upon thethe original sample using the original cluster assignments. Abbreviations. M:

thology, social adjustment and personality correlates of(2010), doi:10.1016/j.schres.2010.01.006

Table 2Comparison of the schizotypy clusters on interview measures of psychopathology — quantitative measures (interview sample n=430).

Cluster

Positive schizotypy Negative schizotypy Mixed schizotypy Low schizotypy F Significant comparisons

n=124 n=117 n=88 n=101 df=3, 426

Global adjustment scale 72.7 (9.8) 73.3 (9.2) 67.7 (11.1) 78.5 (7.8) 20.4*** L>P,N>MPsychotic-like experiences 1.90 (2.39) 0.72 (1.41) 2.36 (2.51) 0.28 (0.84) 26.5*** M,P>N,LNegative symptoms 1.49 (2.41) 4.70 (5.40) 5.38 (4.93) 0.96 (1.87) 33.3*** M,N>P,LSchizotypal symptoms 1.40 (1.81) 0.85 (1.32) 2.10 (2.54) 0.27 (0.65) 20.8*** M>P>N>LSchizoid symptoms 0.30 (0.70) 1.11 (1.86) 1.53 (2.26) 0.15 (0.52) 19.9*** M>N>P,LParanoid symptoms 0.81 (1.58) 0.83 (1.55) 1.63 (2.34) 0.19 (0.70) 12.5*** M>P,N>LAlcohol use 5.31 (6.06) 2.85 (5.08) 3.99 (5.79) 4.04 (5.73) 3.8* P>NAlcohol impairment 1.12 (1.01) 0.69 (0.78) 0.88 (0.77) 0.80 (0.74) 5.6** P>M,N,LDrug use 3.54 (6.19) 0.75 (2.17) 2.33 (5.14) 1.01 (2.48) 10.1*** P>M>N,LDrug impairment 0.96 (1.32) 0.29 (0.73) 0.70 (1.18) 0.41 (0.78) 10.0*** P,M>N,L

***p<.001; **p<.01; *p<.05.Values reflect mean (standard deviation). Post hoc comparisons were computed using Newman–Keuls test.Abbreviations. M: Mixed; P: Positive; N: Negative; L: Low schizotypy.

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marked impairment, including deficits in overall functioningand elevated rates of schizotypic symptoms. Predictablepatterns of deficits were displayed by the positive and negativeclusters. The positive cluster exhibited deficits relative to thenegative and control group on psychotic-like experiences,depression, and substance use and abuse. The negative clusterwas associatedwith deficits in schizoid andnegative symptoms.

3.3. Relationship with questionnaire measures of personalityand social functioning

Table 4 presents the comparison of the four clusters on theSAS and the NEO-PI-R. The mixed cluster demonstrated thegreatest impairment in social functioning. Both thepositive andnegative clusters exhibited impairment relative to the controlgroup; however, the negative cluster's impairmentwas limitedto social and leisure settings. Positive schizotypywas associatedwith increased Neuroticism and decreased Agreeableness andConscientiousness. Negative schizotypy was associated withlower Extraversion, Openness, and Agreeableness relative tothe lowcluster. In general, themixed cluster exhibited themostextreme scores on the Five-Factor domains. The exception was

Table 3Comparison of the schizotypy clusters on interview measures of psychopathology —

Cluster

Positive schizotypy Negative schizotypy

n=124 n=117

Never in a steady relationship 19.4% 32.5%Major depressive episode 28.2% 12.8%Manic episode 2.4% 0.0%Psychiatric treatment:

Hospitalization 4.0% 0.9%Outpatient 27.4% 11.1%Medication 11.3% 5.1%

1st or 2nd ° relativeWith psychosis 4.0% 5.1%With nonpsychotic illness 58.1% 43.6%

Comparisons computed with Fisher's exact test. Alpha=.008.Abbreviations. M: Mixed; P: Positive; N: Negative; L: Low schizotypy.

Please cite this article as: Barrantes-Vidal, N., et al., Psychopschizotypy clusters in a large nonclinical sample, Schizophr. Res.

that the mixed cluster was intermediate to the positive andnegative clusters on Openness, consistent with the notion thatpositive and negative schizotypy are best differentiated by thisdomain.

4. Discussion

4.1. Schizotypy clusters

To our knowledge, this study employed the largest sample ofnonclinically ascertained subjects to explore schizotypy clusters,yielding four clusters characterized by low, high positive, highnegative, and mixed (high positive and negative) schizotypy.This cluster assignment was consistent with the findings fromthe limited cluster studies of schizotypic and schizophrenicsymptoms (e.g., Barrantes-Vidal et al., 2003;Williams, 1994; Vander Does et al., 1993; Williams, 1996). Suhr and Spitznagel(2001a,b) found two different cluster solutions in studies ofcollege students. Using an unselected sample they found clustersdefined primarily by the level of symptom intensity (low,average, high, and a positive/disorganized cluster); whereaswhen using a subsample of high schizotypy scorers, they found

categorical measures (interview sample n=430).

Mixed schizotypy Low schizotypy Significant comparisons

n=88 n=101

30.7% 14.9% N>L19.3% 12.9% P>L,N3.4% 0.0%

5.7% 1.0%28.4% 15.8% P,M>N23.9% 10.9% M>N

6.8% 3.0%59.1% 48.5%

athology, social adjustment and personality correlates of(2010), doi:10.1016/j.schres.2010.01.006

Table 4Comparison of the schizotypy clusters on questionnaire measures of personality and social adjustment (questionnaire sample n=780).

Cluster

Positive schizotypy Negative schizotypy Mixed schizotypy Low schizotypy F Significant comparisons

n=213 n=169 n=107 n=291 df=3, 776

Social adjustment scale §

Total 1.93 (0.31) 1.89 (0.33) 2.11 (0.41) 1.77 (0.30) 31.0*** M>P,N>LStudent 1.92 (0.50) 1.74 (0.44) 2.01 (0.80) 1.72 (0.44) 12.2*** M,P>N,LLeisure 2.00 (0.42) 2.11 (0.52) 2.25 (0.50) 1.88 (0.43) 19.6*** M>N>P>LFamily 1.83 (0.46) 1.76 (0.47) 2.07 (0.67) 1.66 (0.43) 18.9*** M>P,N,L; P>L

NEO-PI-R (T scores)Neuroticism 59.1 (9.1) 54.0 (10.4) 62.3 (10.7) 53.1 (9.1) 33.4*** M>P>L,NExtraversion 57.0 (10.1) 49.2 (11.0) 46.2 (11.4) 59.4 (9.4) 64.8*** L>P>N>MOpenness to Experience 57.7 (11.1) 46.8 (9.8) 53.6 (11.6) 55.9 (10.1) 37.9*** P,L>M>NAgreeableness 40.7 (12.8) 41.5 (11.6) 38.6 (13.0) 46.6 (10.9) 17.0*** L>P,M,NConscientiousness 39.5 (10.9) 43.5 (10.3) 39.6 (12.1) 43.3 (11.2) 7.7*** N,L>M,P

***p<.001; **p<.01;*p<.05.Abbreviations. M: Mixed; P: Positive; N: Negative; L: Low schizotypy.Please note that higher scores reflect worse adjustment on the Social Adjustment Scale.

§ Values reflect mean (standard deviation). Post hoc comparisons were computed using Newman–Keuls test.

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that clusters were defined by the predominance of specificschizotypy features (positive, negative, mixed, and low), not byintensity levels. The difference between their study and thepresent one is that they used the SPQ in the cluster analysis withan unselected sample. It might be argued that themeasurementof positive schizotypy is highly comparable in both studiesdespite the use of different questionnaires. However, the presentstudy also includes an assessment of the negative symptomdimension. As the SPQ was developed to measure schizotypalpersonality disorder, which largely lacks anhedonia (a notablefeature of negative schizotypy), this measure may not haveadequately captured negative symptom traits. Additionally, thelack of clusters defined by the positive and negative schizotypydimensions in the Suhr and Spitznagel (2001a) unselectedsample may indicate that trait-oriented scales are better able tocapture meaningful variation in a nonclinical population thansymptom-oriented scales.

4.2. Validation of clusters: psychopathology, social adjustmentand personality

The positive and negative schizotypy clusters in thepresent study were associated with hypothesized patternsof symptoms and impairment, supporting the validity of theclusters. In terms of schizophrenia-spectrum psychopatholo-gy, the positive schizotypy cluster was characterized byelevated interview-based ratings of psychotic-like, schizoty-pal, and paranoid symptoms compared to the low schizotypycluster. Conversely, the negative schizotypy cluster wasassociated with interview ratings of negative and schizoidsymptoms, as well as paranoid and schizotypal symptoms.This pattern of relationships lends further support to theconstruct validity of positive and negative schizotypy astapped by psychometric inventories in nonclinical samples.Additionally, the mixed schizotypy cluster had the mostdeviant ratings on all these indices, suggesting that thecombination of high positive and negative schizotypic traits isespecially impairing.

The positive, but not negative, schizotypy cluster wascharacterized by heightened substance use and impairment,

Please cite this article as: Barrantes-Vidal, N., et al., Psychopaschizotypy clusters in a large nonclinical sample, Schizophr. Res.

history ofmajor depressive episodes and outpatient psychiatrictreatment, as well as impaired social adjustment. Positiveschizotypy was also associated with impairment in scholasticactivities and interactions. This is striking because the partici-pants were all students and the findings indicated that positiveschizotypes experienced impairment in a primary area offunctioning. The mean five-factor personality scores for thepositive schizotypy cluster were generally within the averagerange. However, the positive schizotypy cluster membersgenerally reported more neuroticism, extraversion, and open-ness than the remaining schizotypic clusters participants, andless agreeableness and conscientiousness than the low schizo-typy cluster members. This profile is consistent with previousfindings reporting higher impulsivity (Dinn et al., 2002) anddrug consumption (Kwapil, 1996) associated with positiveschizotypy, and also with the personality profile of higheropenness and extraversion than negative schizotypy (Kwapilet al., 2008). The positive schizotypy cluster members alsoreported elevated history of major depressive episodes,consistent with a number of previous studies. Using confirma-tory factor analysis, Lewandowski et al. (2006) reported anassociation between positive schizotypy and mood symptomsinnonclinical subjects. Vargheseet al. (2009) found thatodds ofendorsing any psychotic-like symptoms increased in commu-nity individuals with lifetime history of major depressive oranxiety disorder. Likewise, longitudinal studies found thatpositive schizotypy (Chapman et al., 1994) and psychotic-likeexperiences (Verdoux et al., 1999) were associated withelevated rates of mood disorders (at ten-year and one-yearreassessments, respectively). Interestingly, Van Rossum et al.(2009) described that the temporal persistence and clinicalrelevance of psychotic experiences were progressively morelikely with greater level of affective symptoms. The relation ofpositive schizotypy and mood symptoms is consistent withfindings from behavioral genetics studies indicating an in-creased rate of mood disorders in relatives of schizophreniapatients (e.g., Baron and Gruen, 1991). These findingssuggested that theremay be shared genetic and environmentalrisk factors for psychosis anddepression,withdifferences beingquantitative rather than qualitative for mood and non-mood

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psychoses (van Os et al., 1998), consistent with the einheitp-sychosis or unitary psychosis concept that affective and non-affective psychoses lie on a continuum (Crow, 1995).

In addition to schizoidal symptoms, the negative schizo-typy cluster was, as expected, characterized by socialdisconnection and impairment. Participants in the negativeschizotypy cluster were less likely than those in the lowschizotypy cluster to have ever been in a steady romanticrelationship and they reported poorer social adjustment(especially in voluntary social activities such as spendingtime with friends and dating). In terms of personality, thiscluster displayed decreased extraversion, Agreeableness, andOpenness to Experience, consistent with the descriptions byCosta and Widiger (1994).

4.3. What is mixed schizotypy?

An advantage of examining schizotypy clusters instead ofdimensions is that it allows us to classify participants whopresent with both positive and negative schizotypy simulta-neously. Studies using dimensional scores on positive andnegative schizotypy often address this issue by analyzing theschizotypy interaction term; however, this is not the same asdefining a cluster of individuals with a mixed profile. Indeed,the findings in the present paper show that the mixed clusterwas not only themost deviant group, but that they differed oncertain aspects from the pure positive and negative clusters.However, previous analyses using dimensional scores forpositive and negative schizotypy from these subjects foundthat the interaction term was not significant for any of thedependent measures (Kwapil et al., 2008). These contrastingfindings from the same data suggest that the effects ofpositive and negative schizotypy are additive.

The positive and negative schizotypy dimensions have beenhypothesized to have independent heritability and distinctpathophysiologies (e.g., Siever, 1995). Nevertheless, the presentstudy indicates that these dimensions can co-occur, and thattheir coexistence is associatedwith a broader rangeof symptomsand more severe presentation than either dimension individu-ally. This fits with the notion that certain combinations ofbehavior may have a different meaning compared to the samebehaviors considered in isolation (Rutter, 1996). Furthermore,these findings are consistent with the results of Chapman et al.'s(1994) ten-year longitudinal study of schizotypic and controlparticipants. They reported that participants identified bypositive schizotypy (perceptual aberration andmagical ideation)had higher rates of psychosis (5%) than did control participants(1%) and, interestingly, participantswhowere identified by bothpositive (magical ideation) and negative (social anhedonia)schizotypy had a 21% rate of psychosis at the reassessment. Theauthors offered two interpretations for thesefindings.On theonehand, the heightened rates of psychosis in this group might bedue to the fact that social anhedoniamight prevent high positiveschizotypy subjects from obtaining emotional support andtreatment. On the other hand, a syndrome of traits may be amore powerful predictor than a single trait.

The present findings provided additional support for thevalidity of psychometric screening inventories for assessingschizotypy in nonclinical samples previously demonstrated inother samples (e.g., Chapman et al., 1994; Gooding et al., 2005;Kwapil, 1998). The identificationof nonpsychotic schizotypes is

Please cite this article as: Barrantes-Vidal, N., et al., Psychopschizotypy clusters in a large nonclinical sample, Schizophr. Res.

essential for understanding the etiology and development ofschizophrenia and spectrum disorders. Longitudinal studyshould examine whether the mixed schizotypy cluster is atespecially heightened risk for transitioning into clinicaldisorders.

Role of funding sourceNeus Barrantes-Vidal and Thomas R. Kwapil were supported by grants

from the Universitat Autònoma de Barcelona (EME2007-25), the SpanishMinisterio de Ciencia e Innovación (PSI2008-04178), and the Generalitat deCatalunya (2009SGR672).

ContributorsNeus Barrantes-Vidal, PhD, wrote parts of the manuscript and helped in

the design of data analysis. Kathryn E. Lewandowski, PhD, oversaw theimplementation of the study, contributed to the data management and dataanalysis; Thomas R. Kwapil, PhD, designed the study, provided supervision inthe implementation of the study, conducted the statistical analyses, andcontributed to the writing of the manuscript.

Conflict of interestNone of the authors had a conflict of interest.

AcknowledgementsWe thank Martha Diaz and Leigh Dickerson for assistance with data

collection and George O'Toole for assistance with data management.

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